scholarly journals Evolutionary Strategies with Analogy Partitions in P-Guessing Games

2020 ◽  
Author(s):  
Aymeric Vié
Wetlands ◽  
2021 ◽  
Vol 41 (6) ◽  
Author(s):  
Alba Cuena-Lombraña ◽  
Mauro Fois ◽  
Annalena Cogoni ◽  
Gianluigi Bacchetta

AbstractPlants are key elements of wetlands due to their evolutionary strategies for coping with life in a water-saturated environment, providing the basis for supporting nearly all wetland biota and habitat structure for other taxonomic groups. Sardinia, the second largest island of the Mediterranean Basin, hosts a great variety of wetlands, of which 16 are included in eight Ramsar sites. The 119 hydro- and hygrophilous vascular plant taxa from Sardinia represent the 42.6% and 37.9% of the number estimated for Italy and Europe, respectively. Moreover, around 30% of Sardinia’s bryological flora, which is made up of 498 taxa, is present in temporary ponds. An overview at regional scale considering algae is not available, to our knowledge, even though several specific studies have contributed to their knowledge. In order to find the most investigated research themes and wetland types, identify knowledge gaps and suggest recommendations for further research, we present a first attempt to outline the work that has been hitherto done on plants in lentic habitats in Sardinia. Three plant groups (algae, bryophytes and vascular plants), and five research themes (conservation, ecology, inventory, palaeobotany and taxonomy) were considered. After a literature review, we retained 202 papers published from 1960 to 2019. We found that studies on vascular plants, as plant group, were disproportionately more numerous, and inventories and ecology were the most investigated research themes. Although efforts have recently been made to fill these long-lasting gaps, there is a need for updating the existing information through innovative methods and integrative approaches.


Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Victor Massagué Respall ◽  
Stefano Nolfi

We investigate whether standard evolutionary robotics methods can be extended to support the evolution of multiple behaviors by forcing the retention of variations that are adaptive with respect to all required behaviors. This is realized by selecting the individuals located in the first Pareto fronts of the multidimensional fitness space in the case of a standard evolutionary algorithms and by computing and using multiple gradients of the expected fitness in the case of a modern evolutionary strategies that move the population in the direction of the gradient of the fitness. The results collected on two extended versions of state-of-the-art benchmarking problems indicate that the latter method permits to evolve robots capable of producing the required multiple behaviors in the majority of the replications and produces significantly better results than all the other methods considered.


2014 ◽  
Vol 4 (2) ◽  
pp. 20-39
Author(s):  
José L. Guerrero ◽  
Antonio Berlanga ◽  
José M. Molina

Diversity in evolutionary algorithms is a critical issue related to the performance obtained during the search process and strongly linked to convergence issues. The lack of the required diversity has been traditionally linked to problematic situations such as early stopping in the presence of local optima (usually faced when the number of individuals in the population is insufficient to deal with the search space). Current proposal introduces a guided mutation operator to cope with these diversity issues, introducing tracking mechanisms of the search space in order to feed the required information to this mutation operator. The objective of the proposed mutation operator is to guarantee a certain degree of coverage over the search space before the algorithm is stopped, attempting to prevent early convergence, which may be introduced by the lack of population diversity. A dynamic mechanism is included in order to determine, in execution time, the degree of application of the technique, adapting the number of cycles when the technique is applied. The results have been tested over a dataset of ten standard single objective functions with different characteristics regarding dimensionality, presence of multiple local optima, search space range and three different dimensionality values, 30D, 300D and 1000D. Thirty different runs have been performed in order to cover the effect of the introduced operator and the statistical relevance of the measured results


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